Mechanical systems, such as those in which motors are used, are subject to failure due to deterioration of mechanical components. Even before failure, the construction of mechanical systems with rotating parts can produce a significant amount of acoustic noise that is undesirable from the experience of a person using the system. For example, air conditioning systems can provide a more comfortable environment, but can be noisy, such as in room level systems used in hotel rooms and residential bedrooms. As other example, refrigerators, freezers, and water pumps are among other mechanical systems that can generate significant noise during operation.
To reduce the operating noise, system designers have traditionally attempted to reduce the noise by reducing friction, improving the motor mounting, adding sound dampening material, optimizing fan shape, or generating anti-noise, or some combination. Each traditional approach has limits on being able to effectively reduce the operating noise.
In addition to attempting to design for operating noise, some of these traditional approaches have benefits in extending the life of the system. However, for important pieces of equipment, such as mechanical systems including motors used in manufacturing, the cost of a failure can be significant. Thus, the system can be monitored and regularly diagnosed for failure. Such monitoring is traditionally a heavily manual task, with operators at backend servers monitoring operational and usage data to attempt to determine if an aberration exists, and whether it may suggest an imminent failure. However, continual monitoring runs into problems of monitoring frequency, where monitoring too slowly can miss data that would indicate a failure, but monitoring too quickly results in a large amount of data that can be difficult or costly to transmit and store. Additionally, being a largely manual task, constant monitoring of data that does not usually indicate any operation outside of ordinary can “numb” an analyst to important data. Such manual analysis can result in either an excess of false alarms that trigger unnecessary servicing or offlining of equipment, or alarm fatigue resulting in missed diagnoses.
Descriptions of certain details and implementations follow, including a description of the figures, which may depict some or all of the embodiments described below, as well as discussing other potential embodiments or implementations of the inventive concepts presented herein.